scholarly journals Device and Algorithm for Vehicle Detection and Traffic Intensity Analysis

2021 ◽  
Vol 17 (1) ◽  
pp. 83-92
Author(s):  
Mikhail Gorobetz ◽  
Andrey Potapov ◽  
Aleksandr Korneyev ◽  
Ivars Alps
Keyword(s):  
Traffic Flow ◽  
Internal Combustion Engines ◽  
Radio Channel ◽  
Vehicle Detection ◽  
Detection Methods ◽  
Traffic Intensity ◽  
Traffic Light ◽  
Traffic Lights ◽  
Advantages And Disadvantages ◽  
Sensor Module

Abstract To effectively manage the traffic flow in order to reduce traffic congestion, it is necessary to know the volumes and quantitative indicators of this flow. Various detection methods are known for detecting a vehicle in a lane, which, in turn, have their own advantages and disadvantages. To detect vehicles and analyse traffic intensity, the authors use a pulse coherent radar (PCR) sensor module. Testing of various modes of operation of the radar sensor was carried out to select the optimal mode for detecting vehicles. The paper describes a method for fixing vehicles of different sizes, filtering and separating the vehicle from the traffic flow. The developed vehicle detection device works in conjunction with signal traffic lights, through which traffic control takes place. The signal traffic lights, which have their own sensors and control units, communicate with each other via a radio channel; there is no need for cable laying. The system is designed to work on road maintenance sites. The paper describes the experimental data when testing on a separate section of the road. The experiment showed the advantage of traffic lights (cars passed the regulated traffic light faster) from the point of view of calculating the traffic flow over the normal traffic light operation. Reducing downtime in traffic jams, in turn, has a beneficial effect on the environmental situation, since at the moment internal combustion engines prevail in vehicles.

scholarly journals Characteristics of Traffic Flows at Kuda Mati non-traffic light Intersection in Workhour and Holidays

2018 ◽  
Vol 73 ◽  
pp. 08030
Author(s):  
F. Betaubun Herbin
Keyword(s):  
Traffic Flow ◽  
Movement Pattern ◽  
Survey Method ◽  
Traffic Flows ◽  
Traffic Light ◽  
City Center ◽  
Work Time ◽  
Traffic Lights ◽  
Economic Support ◽  
The City

Characteristics of traffic flow needs to be revealed to describe the traffic flow that occurred at the research location. One of the patterns of traffic flow movement of Merauke Regency that is important enough to be observed is the movement pattern that occurs at Kuda Mati Non-traffic lights Intersection. This intersection is one of the access for economic support of Merauke Regency. The intersection connects the city center to the production centers and is used by the community to perform activities in meeting their needs such as working and meeting the needs of clothing, food and shelter. This fulfillment activity is usually differentiated according to work time and holiday time. The method used is survey method to describe the characteristics of traffic flow at the intersection. Data analysis applied MKJI 1997. The results show that peak hour traffic flow occurs at 17.00 - 18.00 on holiday 803 smp / hour, while for working time the traffic flow is evenly distributed with maximum vehicle volume occur at 12:00 to 13:00 which amounted to 471 smp / hour.

scholarly journals Lightweight PVIDNet: A Priority Vehicles Detection Network Model Based on Deep Learning for Intelligent Traffic Lights

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6218
Author(s):  
Rodrigo Carvalho Barbosa ◽  
Muhammad Shoaib Ayub ◽  
Renata Lopes Rosa ◽  
Demóstenes Zegarra Rodríguez ◽  
Lunchakorn Wuttisittikulkij
Keyword(s):  
Deep Learning ◽  
Traffic Control ◽  
Detection System ◽  
Lightweight Design ◽  
Vehicle Detection ◽  
Activation Function ◽  
Urban Traffic ◽  
Vehicle Classification ◽  
Traffic Light ◽  
Traffic Lights

Minimizing human intervention in engines, such as traffic lights, through automatic applications and sensors has been the focus of many studies. Thus, Deep Learning (DL) algorithms have been studied for traffic signs and vehicle identification in an urban traffic context. However, there is a lack of priority vehicle classification algorithms with high accuracy, fast processing, and a lightweight solution. For filling those gaps, a vehicle detection system is proposed, which is integrated with an intelligent traffic light. Thus, this work proposes (1) a novel vehicle detection model named Priority Vehicle Image Detection Network (PVIDNet), based on YOLOV3, (2) a lightweight design strategy for the PVIDNet model using an activation function to decrease the execution time of the proposed model, (3) a traffic control algorithm based on the Brazilian Traffic Code, and (4) a database containing Brazilian vehicle images. The effectiveness of the proposed solutions were evaluated using the Simulation of Urban MObility (SUMO) tool. Results show that PVIDNet reached an accuracy higher than 0.95, and the waiting time of priority vehicles was reduced by up to 50%, demonstrating the effectiveness of the proposed solution.

scholarly journals PATTERNS OF URBAN TRANSPORT FLOWS GENERATION

2020 ◽  
Vol 1 (154) ◽  
pp. 248-252 ◽  
Author(s):  
I. Chumachenko ◽  
A. Galkin ◽  
N. Davidich ◽  
Y. Kush ◽  
I. Litomin
Keyword(s):  
Nervous System ◽  
Travel Time ◽  
Traffic Flow ◽  
Individual Characteristics ◽  
Urban Transport ◽  
Traffic Intensity ◽  
Important Criterion ◽  
Traffic Lights ◽  
The Road ◽  
Expert Opinions

The article is devoted to explaining the issue of exploring the patterns of formation of urban traffic flows in case of the development of urban transport systems projects. Existing methods for predicting traffic flow parameters are developed for all drivers of vehicles, regardless of their individual characteristics, and contain only travel time as a parameter. It is proposed to use the route run, travel time, traffic intensity as the possible criteria, the route runs along the main roads, the condition of the road surface, the number of traffic lights on the route, and fatigue when driving. Based on the results of a questionnaire survey of drivers of individual vehicles, the significance of the criteria for choosing a route of movement for drivers with various types of nervous systems is assessed. The most significant criterion was set up when choosing a route for travel is the “condition of the road surface”. The second most important criterion is “run along the route”. The third criterion was “travel time”. The criterion “traffic intensity” has become even less significant for drivers. The next most important criterion was “the route take place over the main roads”. Even less significant was the criterion “quantity of traffic lights on the route”. The criterion “fatigue during movement” became the least significant. To assess the consistency of expert opinions, a concordance coefficient was used. The values of the concordance coefficient showed that there is a consistency of expert opinions both for the total population of drivers and for their groups, divided on the basis of “temperament”. It was found that when choosing a travel route, drivers are guided by numerous criteria. Moreover, the advantage or disadvantage of one or another criterion depends on its individual characteristics, which are determined by the properties of the central nervous system. Keywords: driver, route, traffic flow, vehicle, questionnaire, nervous system, criterion, significance.

scholarly journals Optimization of Traffic Flow On KS Tubun Street using Greenberg Model

2019 ◽  
Vol 8 (2S7) ◽  
pp. 83-86
Keyword(s):  
Traffic Flow ◽  
Red Light ◽  
Green Light ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
The Road ◽  
Road Users ◽  
Time Parameters

KS Tubun Street is a street in Bogor, which has a fairly high vehicle volume and become one of a high-traffic jam area. This is caused by KS Tubun Street is the main road for road users from Jakarta and Bogor. Traffic jam problem that occurs due to the confluence interchange of traffic flow and traffic lights settings that are not proportional to the volume of vehicles across the road. Optimization of traffic flow at KS Tubun Street performed by the stages of forming a model of traffic flow, determining the density and velocity of the vehicle is based on the Greenberg model, and determining the length of the traffic lights to avoid a buildup of vehicles. The result is a traffic flow model with distance and time parameters. The density of vehicles that occurs on the streets of KS. Tubun street based on the Greenberg model between 180 to 240 unit car of passanger (ucp) with the average velocity of vehicles 15 to 19.5 km per hour. The density of vehicles on KS. Tubun street can be break down by increasing time. Traffic light cycle time can be reduced for 8 seconds with the red light glowing time is 80 seconds and the green light glowing time is 62 seconds.

Proposed Traffic Light Control Mechanism Based on Multi-Agent Coordination

2016 ◽  
Vol 20 (5) ◽  
pp. 803-812
Author(s):  
Satoshi Kurihara ◽  
◽  
Ryo Ogawa ◽  
Kosuke Shinoda ◽  
Hirohiko Suwa ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Urban Areas ◽  
Transport Systems ◽  
Light Control ◽  
Traffic Light ◽  
Agent Based ◽  
Traffic Lights ◽  
Control Framework ◽  
Traffic Light Control ◽  
Multi Agent

Traffic congestion is a serious problem for people living in urban areas, causing social problems such as time loss, economical loss, and environmental pollution. Therefore, we propose a multi-agent-based traffic light control framework for intelligent transport systems. Achieving consistent traffic flow necessitates the real-time adaptive coordination of traffic lights; however, many conventional approaches are of the centralized control type and do not have this feature. Our multi-agent-based control framework combines both indirect and direct coordination. Reaction to dynamic traffic flow is attained by indirect coordination, whereas green-wave formation, which is a systematic traffic flow control strategy involving several traffic lights, is attained by direct coordination. We present the detailed mechanism of our framework and verify its effectiveness using simulation to carry out a comparative evaluation.

scholarly journals Extending the learning and communicating shout-ahead architecture with user-defined exception rules -- a case study for traffic light controls

2021 ◽  
Vol 2 (1) ◽  
pp. 46-67
Author(s):  
Christian Roatis ◽  
Jorg Denzinger
Keyword(s):  
Traffic Flow ◽  
Hybrid Learning ◽  
Learning Approach ◽  
Application Area ◽  
Agent Architecture ◽  
Traffic Light ◽  
Traffic Lights ◽  
Learning Time

We present an extension of the shout-ahead agent architecture that allows for adding human user-defined exception rules to the rules created by the hybrid learning approach for this architecture. The user-defined rules can be added after learning as reaction to weaknesses of the learned rules or learning can be performed with the user-defined rules already in place. We applied the extended shout-ahead architecture and the associated learning to a new application area, cooperating controllers for the traffic lights of intersections. In our experimental evaluations, adding user-defined exception rules to the learned rules for several traffic flow instances increased the efficiency of the resulting controllers substantially compared to just using the learned rules. Performing learning with user-defined exception rules already in place decreased the learning time substantially for all flows, but had mixed results with respect to efficiency. We also evaluated user-defined exception rules for a variant of the architecture that is not using communication and saw similar effects as for the variant with communication. For the communicating version, both variants of adding user-defined exception rules create controllers that are much more flexible than what using the original shout-ahead architecture with its learning is able to create as indicated by experiments with variations of flows.

scholarly journals Minimization of traffic delay in traffic flows with coordinated control

2021 ◽  
Vol 2021 (2) ◽  
pp. 30-41
Author(s):  
Yuriy Royko ◽  
◽  
Yurii Yevchuk ◽  
Romana Bura ◽  
◽  
...  
Keyword(s):  
Traffic Flow ◽  
Coordinated Control ◽  
Signal Duration ◽  
Traffic Intensity ◽  
Traffic Flows ◽  
Light Control ◽  
Traffic Light ◽  
Significant Difference ◽  
Traffic Light Control ◽  
Traffic Delay

The method and results of transport research, carried out by field research method, on the determination of the main indicators of traffic flows with significant unevenness of the movement on the arterial street in conditions of coordinated control is reviewed in the paper. Time parameters of traffic light control for which a reduction in traffic delay is achieved in direct and opposite traffic flow by the change of permissive signal depending on traffic intensity are determined using the simulation method. Change (increase) of the duration of the permissive signal provides uninterrupted movement of vehicles` group during their passage of stop-line at traffic light objects. The proposed method can be used on sections of transport networks with coordinated control, where there is significant heterogeneity of traffic flow, and it prevents the dissipation of groups that consist of vehicles with different dynamic characteristics. Such a result is being performed in the case when in the system of automated control, which combines adjacent intersections on an arterial street, fixed-time program control of traffic light signalization is operating. In this condition, there is a possibility to adjust the duration of signals of traffic light groups by correcting the width (permissive signal duration) and angle of inclination (speed of movement) of the timeline in coordination graphs. The scientific novelty of this research is that the method of traffic delay minimization in conditions of coordinated control acquired further development. The essence of the method is in the controlled change of the range of permissive signal duration in conditions of simultaneous control of the speed of movement between adjacent intersections. Practical value is the application of different programs of traffic light control on sections of arterial streets in transport districts where a significant difference of values of traffic intensity by directions is in morning and evening peak periods.

scholarly journals Recent development of smart traffic lights

2021 ◽  
Vol 10 (1) ◽  
pp. 224
Author(s):  
A’isya Nur Aulia Yusuf ◽  
Ajib Setyo Arifin ◽  
Fitri Yuli Zulkifli
Keyword(s):  
Traffic Flow ◽  
Time Allocation ◽  
Traffic Density ◽  
Light Cycle ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
Smart Traffic ◽  
Very High ◽  
Signal Time

<span id="docs-internal-guid-288f4dcc-7fff-1e8c-0350-5032593b6e4f"><span>Increased traffic flow causes congestion, especially in large cities. Even though congestion is not unusual, traffic jams still result in very high economic and social losses. Several factors cause congestion, one of which is traffic lights. Therefore, a mechanism is needed so that traffic lights can intelligently and adaptively manage signal time allocation according to traffic flow conditions. A traffic light with this type of mechanism is known as a smart traffic light. Smart traffic light cycle settings can be grouped based on the traffic density, scenarios for emergency vehicles, and the interests of pedestrians. This paper analyzes the methods and technologies used in the development of smart traffic light technology from the perspective of these three situations as well as the development of smart traffic light technology in the future.</span></span>

scholarly journals Testing an Adaptive Cruise Controller with coupled traffic and driving simulations

10.29007/84rc ◽  
2019 ◽  
Author(s):  
Mirko Barthauer ◽  
Alexander Hafner
Keyword(s):  
Traffic Flow ◽  
Driving Simulator ◽  
Traffic Simulation ◽  
Traffic Signals ◽  
Simulation Environment ◽  
Cruise Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Subjective Judgement ◽  
Traffic Simulations

In many cases, driving simulator studies target how test persons interact with surround- ing traffic and with traffic signals. Traffic simulations like SUMO specialize in modeling traffic flow, which includes signal control. Consequently, driving and traffic simulation are coupled to benefit from the advantages of both. This means that all except the driven (ego) vehicle are controlled by the traffic simulation. Essential vehicle dynamics data are exchanged and applied frequently to make the test person interact with SUMO-generated traffic. Additionally, traffic lights are controlled by SUMO and transferred to the driving simulation. The system is used to evaluate an Adaptive Cruise Control (ACC) system, which considers current and future traffic light states. Measures include objective terms like traffic flow as well as the subjective judgement of the signal program, the ACC and the simulation environment.

scholarly journals CELLULAR AUTOMATA SIMULATION OF TRAFFIC LIGHT STRATEGIES IN OPTIMIZING THE TRAFFIC FLOW

2005 ◽  
Vol 4 (2) ◽  
pp. 13
Author(s):  
E. H. NUGRAHANI ◽  
R. RAMDHANI
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Control Strategies ◽  
Velocity Model ◽  
Flow Density ◽  
Traffic Light ◽  
Cellular Automata Model ◽  
Optimal Velocity ◽  
Traffic Lights ◽  
Traffic System

The behavior of traffic system controlled by traffic lights is presented under assumptions of city traffic on a single lane based on the optimal velocity model.  The effect of differrent traffic light control strategies on the traffic flow is discussed using three different strategies, i.e. the synchronized, green wave, and random offset strategies. The flow-density diagrams are analyzed using these strategies.   The numerical investigation is carried out using cellular automata model to get a better understanding of the microscopic behavior of the system under the three different traffic light strategies.

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